The Breakthrough That Changed AI’s Direction
On September 12, 2024, OpenAI introduced a fundamentally new approach to artificial intelligence with the launch of its o1 model series. Unlike previous large language models that generated immediate responses, o1 was designed to “think before answering”—spending additional compute time on internal reasoning before producing outputs. This represented what OpenAI described as a new paradigm: models trained with reinforcement learning to refine their thinking process through chain-of-thought reasoning.
“We trained these models to spend more time thinking through problems before they respond, much like a person would,” OpenAI explained in their announcement blog post. The initial release included two variants: o1-preview, the full-capability model, and o1-mini, a faster and more cost-effective version optimized for coding tasks.
Unprecedented Performance on Complex Tasks
The performance benchmarks released alongside o1 marked a dramatic leap forward in AI capabilities, particularly in mathematics and scientific reasoning. According to OpenAI’s system card, o1 achieved 83% accuracy on the International Math Olympiad (IMO) qualifying exam—a striking improvement over GPT-4o’s 13% score on the same test.
The scientific reasoning capabilities proved equally impressive. OpenAI reported that o1 performed at PhD-level accuracy on benchmarks testing physics, biology, and chemistry knowledge. On the GPQA Diamond benchmark, designed to test graduate-level scientific reasoning, o1 significantly outperformed its predecessors.
For competitive programming, o1 reached the 89th percentile in Codeforces competitions, demonstrating sophisticated problem-solving abilities that extended well beyond pattern matching or memorization.
The Trade-off: Speed for Accuracy
The o1 models introduced a notable trade-off that distinguished them from previous AI systems. Responses took considerably longer to generate—sometimes tens of seconds rather than the near-instantaneous replies users had grown accustomed to with GPT-4. This delay reflected the model’s internal reasoning process, during which it explored different approaches and refined its thinking.
Crucially, OpenAI chose not to expose the full chain-of-thought reasoning to users. Instead, users saw only a simplified summary of the model’s thinking process. This decision sparked immediate discussion in the AI research community about transparency and interpretability, though OpenAI cited both competitive considerations and safety concerns in their explanation.
A Strategic Shift in AI Development
The launch of o1 signaled a fundamental strategic shift in AI development: from scaling pre-training compute to scaling inference-time compute. Rather than simply building larger models with more training data, o1 demonstrated that allowing models to “think longer” during inference could unlock dramatic capability improvements.
OpenAI CEO Sam Altman characterized the significance of this moment in ambitious terms. “We’re beginning to see a path to AGI,” he stated, suggesting that the reasoning capabilities demonstrated by o1 represented meaningful progress toward artificial general intelligence.
Industry Context and Competitive Landscape
The o1 release came at a pivotal moment in the AI industry. By September 2024, multiple companies had released competitive large language models, and improvements in raw benchmark scores had begun to plateau. OpenAI’s approach of investing compute during inference rather than solely during training offered a new axis of competition.
The timing also followed months of speculation about OpenAI’s “Strawberry” project, which had been rumored throughout mid-2024. Industry observers had anticipated a reasoning-focused model, and o1’s release confirmed these expectations while exceeding many predictions about its capabilities.
Initial Limitations and Scope
OpenAI was transparent about o1’s current limitations. The models lacked several features present in GPT-4o, including web browsing capabilities and image processing. The o1-preview version was also significantly more expensive than previous models, reflecting the additional compute required for its reasoning process.
Access to o1 was initially limited to ChatGPT Plus and Team subscribers, with API access available to developers in usage tier 5. This staged rollout suggested OpenAI was carefully managing the deployment of what it considered a particularly powerful system.
A Watershed Moment
The week following o1’s launch saw widespread technical analysis and commentary from AI researchers and practitioners. The model’s performance on mathematical and scientific reasoning tasks suggested that architectural innovations and training techniques—not just scale—could drive meaningful capability improvements.
Whether o1 would prove to be a stepping stone toward AGI or simply another incremental improvement remained hotly debated. But by September 19, 2024, one thing was clear: OpenAI had demonstrated a new approach to AI development that would influence the industry’s direction for years to come.